scholarly journals Determining the Rating of Ukrainian Banks on the Risk of Legalization of Illegally Obtained Income

2020 ◽  
pp. 31-45
Author(s):  
Serhii V. Lyeonov ◽  
Olha V. Kuzmenko ◽  
Serhii V. Mynenko ◽  
Aleksy S. Kwilinski ◽  
Oleksii V. Lyulyov
Keyword(s):  
Money Laundering ◽  
Input Data ◽  
Methodological Approach ◽  
Optimal Number ◽  
Data Set ◽  
Minkowski Metric ◽  
Number Of Factors ◽  
Financial Monitoring

The article examines a scientific and methodological approach to the rating of banks on the risk of money laundering. A sample of 18 indicators of 65 Ukrainian banks in 2019 was selected. The relative indicators that characterize the risk of using the bank's operations to legalize illegal income are considered. Logically, the indicators are divided into three parts. The first group of indicators characterizes the quantity and quality of the bank's compliance with the current legislation of Ukraine in the field of financial monitoring. The second group of indicators reflects the size of cash turnover in the bank, which is a characteristic of the bank's participation as a conversion center. The third group of indicators characterizes the bank's involvement in international income laundering cycles, considering transactions in countries - offshore zones and dubious transactions without explicit confirmation by a foreign trade contract. The study of input data on multicollinearity was carried out, based on which 5 indicators that are collinear with others were excluded. Normalization of the input data set based on nonlinear normalization is carried out. The weights of each indicator are calculated based on the principal component’s method. The optimal number of factors was determined based on the percentage of the variance explained by each factor and the graph of the scree plot. Minkowski metric was used to construct the integral index. Based on the integrated indicator, the rating of banks on the risk of money laundering was formed. The verbal-numerical Harrington scale provided a qualitative characterization of the risk of using bank operations to legalize illicit income. MS Office Excel software and Correlations of the statistical package STATISTICA 10 were used for calculations. Keywords: Anti-money laundering, the rating of banks, on the risk of legalization, integral indicator, Minkowski metric.

scholarly journals Perceived quality assessment of the health services offered to riverine communities in Brazilian Amazon

2020 ◽  
Vol 8 (11) ◽  
pp. 360-374
Author(s):  
Duarcides Mariosa ◽  
Pedro Mariosa ◽  
Orandi Falsarella ◽  
Renato Ferraz ◽  
Henrique Pereira
Keyword(s):  
Sustainable Development ◽  
Health Services ◽  
Methodological Approach ◽  
Field Research ◽  
Original Data ◽  
Performance Standard ◽  
Access To Health Services ◽  
Data Set ◽  
The Impact

In line with the UN Agenda 2030 Sustainable Development Goals, Public Health Policies follow in Brazil criteria of universality, completeness, and equity formulated to ensure access to health services in adequate quantity and quality for the entire population. To evaluate the quality of services provided in health units, it is essential, however, to make methodological considerations to concern the use of proper instruments and techniques to achieve accuracy and precision regarding their effectiveness for the user population. Mainly where health care is precarious or in need of adjustment, properly constructed indicators can become excellent management tools. This paper aims to analyze the specificities of the perception of the quality of health services offered to residents of the riverside communities of the Tupé Sustainable Development Reserve (SDR), Manaus, Amazonas, Brazil. The methodological approach is from a descriptive and ecological case study, based on field research with original data collection of fixed residents, aged over 18 years, by applying structured questionnaires and analyzing the results according to the SERVQUAL methodology. In the present study, it observed the impact of previous experiences of attending on the quality of health service. In the case of SDR of Tupé, there were positive evaluations with above 70% in all items. Still, when analyzing the data set and cut, considering the existence or not of previous experience, a different pattern of perception was detected. Based on these results, we suggest that the quality perception of health has to do with competitiveness, associated with the performance standard on the offer available to the customer.

Improving the estimates of nitrate concentrations at subsurface drained agricultural catchment scale using a new conceptual water quality model

2021 ◽  
Author(s):  
Julien Tournebize ◽  
Samy Chelil ◽  
Hocine Henine ◽  
Cedric Chaumont
Keyword(s):  
Water Quality ◽  
Soil Profile ◽  
Model Calibration ◽  
Input Data ◽  
Performance Criteria ◽  
Time Step ◽  
Data Set ◽  
Calibration And Validation ◽  
Nitrate Concentrations

<p>The agricultural source pollution, such as nutrient and pesticides, affect the quality of surface water and groundwater. The agricultural nonpoint source pollution due to the excessive land fertilization is considered by researchers and governments as a concerning and sensitive issue. At the scale of agricultural catchments, the modeling of nitrate-leaching losses has been widely addressed in several studies. However, most of developed models require a large number of input data and parameters. Some of them include a complex process of biogeochemical nitrogen process or a full agronomic module and could be computationally time-consuming. Moreover, the quality of the input data makes the model calibration less efficient.</p><p>The objective of this study is to present a new conceptual and reservoir model (SIDRA-N), developed to better access the time-variation of nitrate concentrations [NO3-] at the outlet of subsurface drainage network. The model represent a simplified scheme of subsurface flow and nitrate transfer processes in the soil profile, between the drain and the mid-drain. The soil profile is decomposed into three interconnected compartments: the first compartment represents the rapid transfer of water and nitrate through the soil macroporosity; the two other compartments describe the progressive contribution of the horizontal transfer.</p><p>The input data to the nitrate module consists on the Remaining pools of Nitrate at the Beginning of Winter season (RNBW), introduced before the winter of each hydrological year. This value should represent all biogeochemical transformations of nitrogen and agricultural practices from previous crop. This variable can explain until 80% of the total nitrate flux exported yearly. Hence, SIDRA-N model requires only two input variables: the drainage discharge and the RNBW. A set of parameters was introduced to regulate nitrate fluxes and discharge transiting through compartments to the drain outlet.</p><p>Calibration and validation (C/V) procedures are fundamental to the assessment of the performance and the robustness of water quality models. In this study, the split sample test for the model calibration and validation (C/V) was carried out using data set from Rampillon study site (355 ha, data for 6 years), located East of Paris, in France. The C/V step was performed using high frequency observations (hourly time-step) of nitrate concentrations and drainage discharge. The results showed performance criteria of KGE greater than 0.5 and RMSE less than 5 mgN/l. These results confirm the very good quality of simulations. Finally, a seasonal model calibration was implemented to observe the yearly parameter variability and ensure the model stability and consistency.</p>

scholarly journals No Neuron Left Behind: A genetic approach to higher precision topological mapping of self-organizing maps

2015 ◽  
Vol 5 (1) ◽  
pp. 1-12
Author(s):  
Chris Gorman ◽  
Clint Rogers ◽  
Iren Valova
Keyword(s):  
Pattern Recognition ◽  
Input Data ◽  
Topological Representation ◽  
Genetic Approach ◽  
Self Organizing Maps ◽  
Data Set ◽  
Running Time ◽  
Left Behind ◽  
Self Organizing

AbstractSelf-organizing maps are extremely useful in the field of pattern recognition. They become less useful, however, when neurons fail to activate during training. This phenomenon occurs when neurons are initialized in areas of non-input and are far enough away from the input data to never move toward the input. These neurons effectively misrepresent the data set. This results in, among other things, patterns becoming unrecognizable.We introduce an algorithm called No Neuron Left Behind to solve this problem.We show that our algorithm produces a more accurate topological representation of the input space.We also show that no neuron clusters form in areas of noninput and that mapping quality of the SOM increases drastically when our algorithm is implemented. Finally, the running time of NNLB is better or comparable to classic SOM without it.

Suicide in New South Wales Prisons, 1995–2005: Towards a Better Understanding

2007 ◽  
Vol 41 (6) ◽  
pp. 519-524 ◽  
Author(s):  
Colmán O'Driscoll ◽  
Anthony Samuels ◽  
Mark Zacka
Keyword(s):  
New South ◽  
New South Wales ◽  
Rare Event ◽  
Data Set ◽  
The Past ◽  
South Wales ◽  
Number Of Factors ◽  
Prison Environment ◽  
Deaths In Custody

Objectives: This paper reports on a review of suicides in New South Wales (NSW) prisons from 1 January 1995 to 31 December 2005 in an attempt to gain a better understanding of the nature and quality of the problem of suicide among prisoners. Method: All deaths in NSW prisons for the period were reviewed. Those identified as self-inflicted, with a coronial finding of death by suicide or those awaiting a coronial hearing but reported as possible death by suicide were included. A data set was collected on each case and entered into a database. Results: A total of 92 cases were identified as deaths by suicide in NSW prisons from 1 January 1995 to 31 December 2005, representing 41% of all deaths in custody for the period. Conclusion: The rate of suicide in NSW prisons has been declining over the past 10 years, but remains approximately 10-fold that of the NSW community. Suicide was the leading cause of death among NSW inmates from 1995 to 2005. Suicide is a rare event, making its prediction a difficult task, with the prison environment a further compounding factor. This review highlights a number of factors, which appear to be common in many cases. Increased monitoring during the first week of incarceration may be an effective intervention. It is recommended that consideration be given to the length of time spent on remand and the value of custodial sentences of ≤6 months.

scholarly journals The role of the coercive influence method in improving the legal regulation of administrative coercion measures

2021 ◽  
pp. 71-79
Author(s):  
A. I. Kaplunov
Keyword(s):  
Police Officers ◽  
Methodological Approach ◽  
Legal Regulation ◽  
Theoretical Level ◽  
Structural Units ◽  
Coercive Measures

The legal regulation of administrative coercion measures as the basic structural units of administrative coercion is considered in the article through the prism of the concept of "method of coercive influence", which is the key, essential for the characterization of the content of the administrative coercion measure, and the elements that determine the legality of its application. The chosen methodological approach allowed the author to assess at a deeper theoretical level the quality of the legal regulation of certain administrative enforcement measures used by the police, and to identify the shortcomings associated with the consolidation in the legislation of the method of coercive influence of such coercive measures as the use of physical force and firearms, suspension from driving a vehicle, to identify problematic issues in the use of firearms by police officers, due to the regulation of the grounds, the procedure and conditions for the implementation of this method of coercive influence. A variant of the concept of "resistance" is proposed to eliminate the gap in the current legislation.

scholarly journals BANKING IN DIGITAL AGE: EFFICIENCY OF АNTI-MONEY LAUNDERING SYSTEM

2021 ◽  
Vol 2 (37) ◽  
pp. 4-13
Author(s):  
S. Lieonov ◽  
T. Vasilyeva ◽  
S. Mynenko ◽  
T. Dotsenko
Keyword(s):  
Utility Function ◽  
Money Laundering ◽  
Input Data ◽  
Statistical Significance ◽  
Nonlinear Function ◽  
The State ◽  
Criminal Offenses ◽  
Financial Monitoring ◽  
Monitoring Service ◽  
Financial Transactions

Abstract. The article is devoted to the problems of the development of a system for combating the legalization of income obtained illegally in the context of digitalization of banking activities. The concept of the effectiveness of the anti-money laundering system was considered. The expediency of using the utility approach for modeling the effectiveness of the system for combating money laundering has been determined. The indicator of the effectiveness of the system of combating money laundering was chosen as the share of indictments sent to the court in the total number of criminal offenses for which pre-trial investigation was carried out in the corresponding period. The first alternative of choice — the focus on the development of identifying suspicious financial transactions is characterized by the indicator Share of criminal offenses for which pre-trial investigation was carried out per one transaction report submitted to the State Financial Monitoring Service. The second alternative of choice — the development of innovative technologies, is characterized by the indicator of the Level of digitalization of the economy. The input data are the indicators on the crime rate in Ukraine, the work of the pre-trial investigation bodies, obtained from the State Financial Monitoring Service of Ukraine, the General Prosecutor's Office of Ukraine and the State Statistics Service of Ukraine, suspicious financial transactions and the number of Internet subscribers. On the basis of the calculated autocorrelation coefficients of zero differences and determination of their statistical significance, a nonlinear function of the relationship between mictoramas was selected. Using the Stone-Geary utility function, which for the selected input data took the form of a Cobb-Douglas power function, the degree of response of alternative approaches to improving the effectiveness of the system of combating criminal proceeds was determined. The degree of digitalization of the economy has a high level of elasticity. Therefore, to increase the effectiveness of the system of combating money laundering, it is necessary to develop innovative information technologies in the field of FinTech. Keywords: bank, countering the legalization of criminal proceeds, the utility function of Stone-Geary, the Cobb-Douglas function, the effectiveness of combating the legalization of criminal proceeds, the digitalization of the economy. JEL Classification C49, O17, O33, G21, G14 Formulas: 4; fig.: 5; tabl.: 0; bibl.: 32.

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

Physicochemical and bacteriological characterization of hospital effluents and their impact on the environment

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Human Health ◽  
Fecal Coliforms ◽  
Chemical Pollution ◽  
Hospital Effluents ◽  
Biological Contaminants ◽  
Almost All ◽  
Direct Discharge ◽  
Significant Chemical

Liquid effluents discharged by hospitals may contain chemical and biological contaminants whose main source is the different substances used for the treatment of patients. This type of rejection can present a sanitary potentially dangerous risk for human health and can provoke a strong degradation of diverse environmental compartments mainly water and soils. The present study focuses on the quality of the liquid effluents of Hassani Abdelkader’s hospital of Sidi Bel-Abbes (West of Algeria). The results reveal a significant chemical pollution (COD: 879 mgO2/L, BOD5: 850 mgO2/L, NH4+ : 47.9 mg/l, NO2- : 4.2 mg/l, NO3- : 56.8 mg/l with respect to WHO standard of 90 mgO2/L, 30 mgO2/L, 0.5 mg/l, 1 mg/l and 1 mg/l respectively). However, these effluents are biodegradable since the ratio COD/BOD5 do not exceeded the value of 2 in almost all samples. The presence of pathogen germs is put into evidence such as pseudomonas, the clostridium, the staphylococcus, the fecal coliforms and fecal streptococcus. These results show that the direct discharge of these effluents constitutes a major threat to human health and the environment.

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